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EXTERNAL ADJUSTMENT WITH A COMMON CURRENCY: THE CASE OF THE EURO AREA

Alberto Fuertes

Documentos de Trabajo N.º 1936

2019

EXTERNAL ADJUSTMENT WITH A COMMON CURRENCY: THE CASE

OF THE EURO AREA

Documentos de Trabajo. N.º 1936

2019

(*) The views in this paper are those of the author and do not represent the views of the Banco de España or the Eurosystem.(**) E-mail: [email protected]

Alberto Fuertes (**)

BANCO DE ESPAÑA

EXTERNAL ADJUSTMENT WITH A COMMON CURRENCY:

THE CASE OF THE EURO AREA (*)

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© BANCO DE ESPAÑA, Madrid, 2019

ISSN: 1579-8666 (on line)

Abstract

This paper analyzes the behaviour of the external adjustment path for the four main economies

in the euro area. I fi nd a structural break in the behaviour of the net external position at the

time of the introduction of the euro for France, Italy and Spain, pointing out that the inception

of the common currency changed their external adjustment process. Germany does not

show this structural break, being its external position more affected by other events such as

the country reunifi cation in 1989. I also fi nd that France and Italy will adjust the net external

position mainly through the valuation component, while Germany and Spain will restore their

external balance mostly through the trade component. The common currency area could

have exacerbated Germany’s net creditor position as the evolution of the euro has reacted

to the external adjustment needs of debtor countries such as Italy and Spain.

Keywords: external adjustment, exchange rate regime, structural breaks, valuation

adjustment.

JEL classifi cation: F31, F33.

Resumen

Este trabajo analiza el comportamiento de la posición fi nanciera externa de las cuatro

principales economías de la zona del euro, y si la introducción de la moneda única ha

modifi cado su evolución. Se documenta una ruptura estructural en el comportamiento de

la posición externa neta de Francia, Italia y España en el momento de la introducción

del euro, que señala que la creación de la moneda única cambió el proceso de ajuste

externo en estos países. Alemania, sin embargo, no experimentó esta ruptura estructural

y su posición externa se ha visto más afectada por otros eventos, como la reunifi cación del

país en 1989. Los resultados empíricos muestran que Francia e Italia ajustarán sus

desequilibrios externos principalmente por medio del componente de valoración, mientras

que en Alemania y España primará el componente de comercio. El área monetaria común

puede haber fomentado el incremento en la posición acreedora de Alemania, ya que el

comportamiento de la moneda única ha estado condicionado por las necesidades de ajuste

externo de países deudores como Italia y España.

Palabras clave: ajuste externo, régimen de tipo de cambio, cambio estructural, componente

de valoración.

Códigos JEL: F31, F33.

BANCO DE ESPAÑA 7 DOCUMENTO DE TRABAJO N.º 1936

1The U.S., for instance, had a negative IIP representing 39% of its GDP at the end of 2017.2In absolute terms Spain holds the second largest net external debtor position in the world amounting

941.507 billion euros (1.108.386 billion dollars). The US is the country with the largest negative net externalposition totaling 7.725.002 billion dollars.

1 Introduction

liabilities denominated in different currencies (valuation component) and also of affecting

future net exports (trade component). Lane and Shambaugh (2010) do also emphasize the

impact of currency movements on the external positions for a large sample of countries. They

find that the wealth effects associated with exchange rate changes are substantial and can

explain a sizeable share of the overall valuation shocks that hit the net foreign asset position.

Moreover, Fuertes (2019) shows the importance of the nominal exchange rate regime for the

process of external adjustment in the US. He finds that the collapse of the Bretton Woods

The process of external adjustment within a common currency area has received little at-

tention in the literature, despite the fact that an important mechanism of correction of

imbalances, the nominal exchange rate, has been partially cancelled. The lack of nominal

exchange rate adjustment for the bilateral transactions and external positions among the

countries of the currency area may difficult the reduction of large net external liability posi-

tions. As an alternative, the more complicated and slower process of adjustment in product

prices and wages (internal devaluation) may operate in the absence of the nominal foreign ex-

change. Keeping the net external position under control is crucial given that economies with

large net liability positions are more vulnerable to capital markets disruptions and growing

imbalances may trigger sustainability problems. These vulnerabilities were evident during

the global financial crisis and the subsequent euro area crisis, as several economies experi-

enced sudden stops, sovereign debt problems, or both. Moreover, recent research by Gadea

et al. (2018) shows how external imbalances also affect the business cycle, as economies with

large external imbalances experience slower recoveries.

At the end of 2017 the international investment position (IIP) of the euro area, the largest

common currency union in the world, recorded a net liability position of 388 billion euros,

representing 3.5% of its GDP. Even though this is almost a balanced position1 there are large

differences among countries, which have become even larger after the inception the euro in

1999. For instance Germany amounts a net external creditor position representing 59% of

its GDP at the end of 2017 while Spain shows a net debtor position representing 81% of its

GDP2. Peripheral countries face the largest net liabilities positions in the euro area, with

Portugal, Greece and Ireland showing net external positions representing 105.8%, 140.9%

and 148.3% of its GDP respectively (see Chart 1).

The process of external adjustment for the countries within the euro area is different because

these economies share a common currency. Gourinchas and Rey (2007) show that the dy-

namics of the exchange rate play a major role in the external adjustment process of the US

since it has the dual role of changing the differential in rates of return between assets and


3There may be second order effects as the depreciation could affect the terms of trade with the countriesoutside the currency area.

system of fixed exchange rates in 1973 affected the behaviour of the US net external posi-

tion, implying an increase in the importance of the valuation component during the floating

period. Given all the previous empirical evidence, it is expected that the inception of the

common currency may have affected the external adjustment process for the countries of the

euro area.

The introduction of the euro made the effects of nominal exchange rate changes to disappear

among the countries in the currency area. First, a net debtor country could not rely anymore

on foreign exchange depreciations to reduce the relative value of the local currency external

debt held with other countries of the currency union. Similarly, a currency depreciation will

not have any direct impact on the bilateral trade among the countries with the same currency3. Second, the behaviour of the exchange rate may not favour the external adjustment

of all countries in the currency area, as foreign exchange movements will respond to the

macroeconomic and monetary conditions of the whole currency union. For instance, a debtor

country within the union that would benefit from an exchange rate depreciation to improve

its external position may face an appreciating currency due to the macroeconomic situation

of the other countries and the current monetary policy of the central bank. Because of these

two reasons, changing from a floating to a fixed exchange rate regime within a common

currency area may difficult the external adjustment and could be potentially dangerous for

countries with large negative external positions. Understanding how the external adjustment

process has evolved over time for the countries of the euro area and the implications of the

introduction of the euro for that process are the main research questions of the paper.

This work is related to the studies analyzing the external adjustment process, with an em-

phasis on the relevance of valuation effects and the nominal exchange rate regime. Friedman

(1953) initiated the debate arguing that flexible exchange rates facilitate the correction of

external imbalances by allowing an automatic adjustment in a context of nominal rigidities.

Following this idea several studies have analyzed empirically the validity of this assumption

by investigating how current account imbalances are corrected depending on the exchange

rate regime. Gosh et al. (2014) find a robust relationship between the exchange rate regime

and the speed of external adjustment confirming Friedman´s hypothesis. Similarly, Eguren-

Martin (2016) finds evidence that flexible exchange rate arrangements deliver faster current

account adjustment among non-industrial countries. Fuertes (2019) focuses on the conse-

quences of a change in the exchange rate regime for the behaviour of the net external position,

being the first study to analyze the adjustment of the net external imbalance instead of only

focusing on the current account. He finds that the behaviour of the U.S. net external position

changed at the end of the Bretton Woods system of fixed exchange rates in 1973, with the

U.S. external imbalance increasing its variance and turning into a debtor position during

the floating period. He also finds that the exchange rate regime affects the U.S. external


adjustment process mainly through the valuation channel, which increased its relevance over

the floating period. Previously, Gourinchas and Rey (2007) had already documented the

importance of the valuation component for the external adjustment process, finding that

this component explained 27% of the variance for the cyclical part of the US net external

position. Further analysis by Evans and Fuertes (2011) and Evans (2012) show that the

contribution to the external adjustment of the valuation component is larger than that of

the trade component when analyzing the whole U.S. external imbalance and not only its

cyclical part. Theoretical models have also emphasized the role of valuation effects on the

dynamics of the net external position. Devereux and Sutherland (2010) present a DSGE

model with portfolio choice capable to reproduce the dynamics of the valuation channel of

external adjustment. The model can only generate unexpected valuation effects, being the

anticipated ones small and reproduced at higher orders of approximation. Ghironi et al.

(2015) also examine the valuation channel of external adjustment theoretically in a DSGE

model, being able to separate asset prices and quantities in the definition of net foreign assets.

This is more consistent with previous empirical work that has documented the relevance of

expected valuation effects (see Gourinchas and Rey (2007), Evans and Fuertes (2011) and

Evans (2012)).

In this paper I analyze the external adjustment path of the four main economies of the euro

area, covering both the period before and after the introduction of the euro, to understand

how the currency area affected the external adjustment process. In principle, the incep-

tion of the euro should have limited the capacity of the nominal exchange rate to correct

external imbalances. This is evident as most of the research related to the correction of

external imbalances in euro area countries has focused on the process of internal devaluation

and its consequences, acknowledging the limited role of the nominal exchange rate. Differ-

ent studies have analyzed theoretically and empirically how current account deficits should

be transformed into surpluses by a combination of a decrease in domestic spending, real

exchange rate depreciation and a reduction in unit labor costs4.

To the best of my knowledge this is the first attempt to study the behaviour of the net

external position for a set of euro area countries, including debtor and creditor countries,

and analyzing the implications of the common currency area for their external adjustment

paths. Within this framework the main contributions of the paper are the following: First

I build a novel data set of quarterly positions on assets and liabilities for the categories of

equity, fixed income, direct investment and other assets/liabilities for France, Germany, Italy

and Spain. The data set also includes estimates of quarterly total returns and capital gains

for each of those categories. Second, I find a structural break in the behaviour of the net

external position for France, Italy and Spain at the time of the introduction of the euro,

pointing out that the inception of the common currency changed the external adjustment

4See for example Atoyan et al. (2013), Kang and Shambaugh (2014), Eggertsson et al. (2013) or Andreset al. (2018).


process. The fact that Germany does not show this structural break is consistent with

the exchange rate regime mainly affecting the valuation channel of external adjustment,

given that the variance of Germany’s net external position is almost completely explained

by the trade channel. I also find a structural break for the external imbalances of Spain

and Italy during the crisis of the European Exchange Mechanism (ERM) in 1992. Over

this period the Italian lira and the Spanish peseta were devaluated and Italy abandoned

the ERM. The importance of the valuation component of external adjustment increases

after the introduction of the euro for France and Italy, and decreases for Germany and

Spain. Third, I also find that France and Italy will adjust the net external position mainly

through the valuation component of external adjustment, while Germany and Spain will

restore their external balance mostly through the trade component. Both the valuation and

trade components have supported the evolution of the net external position in France, Italy

and Spain. In the case of Germany the valuation component has limited the overall trend

towards a larger creditor position, which has been driven by the trade component. Fourth,

in the absence of unexpected shocks, the half-live of the external imbalances is relatively

short as Germany and Spain, the two countries with the largest imbalances, will be able to

reduce their creditor and debtor positions by half in 7 and 3 years respectively. Finally, I

documented asset pricing implications as the net external position has explanatory power

over the future evolution of the exchange rate. A deterioration in the external imbalance of

France, Italy and Spain implies a future depreciation of the euro, facilitating the external

adjustment through the trade component. On the contrary, for Germany, the behaviour of

2 Data

The data set includes information for France, Germany, Italy and Spain about their inter-

national investment position (IIP) as well as the external portfolio returns for assets and

liabilities each period. The IIP data comes from the Balance of Payments Statistics (BOPS)

of the IMF. Using the original data I obtain asset and liabilities positions for different cat-

egories: equity, direct investment, fixed income and other assets/liabilities. The data set is

constructed following the same methodology employed by Gourinchas and Rey (2007). The

IIP data from the BOPS comes on a quarterly frequency only for the more recent years and

I estimate quarterly positions using portfolio flows and total returns to increase the sample

the common currency has hindered the external adjustment as it has supported the increase

in its creditor position.

The paper proceeds as follows: Section 2 presents the data set. Section 3 includes most of

the empirical analysis, including the structural break tests, the estimation of the valuation

and trade components and asset pricing implications. Section 4 develops robustness checks

regarding the calculation of the portfolio returns and Section 5 concludes.


period 5 . It is important that the data set include the years before and after the inception

of the euro in order to fully characterise the changes triggered by the introduction of the

common currency.

The other important part of the data set are the portfolio returns. The returns are com-

puted from market prices for each of the asset/liabilities classes: equity, direct investment,

fixed income and other assets/liabilities. In order to identify the market weights within

the categories of equity, direct investment and fixed income6 I use the Coordinated Direct

Investment Survey (CDIS) and the Coordinated Portfolio Investment Survey (CPIS), both

from the IMF. Once I have the market weights for each quarter and asset category I calculate

total returns and capital gains for each market and compute the total portfolio return for

the different categories using the market weights. For example, for the equity assets cate-

gory, I get from the CPIS the value of equity assets held in each foreign country to obtain

5The data availability of the IIP at the quarterly and yearly frequency is different for each country, withthe final estimated quarterly samples spanning from 1980: IV to 2017: I for Germany, Italy and Spain. ForFrance the sample begins on 1989:III.

6For “other assets” I use the same market weights as those computed for short-term fixed income assets.For “other liabilities” I assume the total value is denominated in local currency using the same returns asthose from short term fixed income liabilities.

geographical weights that will be used together with the returns of the corresponding bench-

mark equity index to compute the total return. The information contained in the market

weights is also important because we can assess the portfolio value of the positions held with

the other countries of the currency area. Chart 2 shows the percentage of foreign equity

assets held in euro area countries for the four countries of analysis. As we can see all of them

hold a relevant share of their equity assets portfolio in the euro area. Even though there

is no information about euro area equity weights before 2001 it is reasonable to think that

the introduction of the common currency may have changed the behaviour of capital gains.

Before the introduction of the euro capital gains were determined both by asset prices and

foreign exchange movements. After the introduction of the euro much of the capital gains

coming from the equity assets portfolio were not affected by nominal exchange rate changes,

being mainly determined by asset price changes7. This may have also affected the size and

direction of external wealth effects, modifying the behaviour of the valuation channel of

external adjustment.

I complete the data set with information on imports and exports for each country8. We can

asses the relevance of the commercial ties the four countries of analysis have with the rest

of the euro area members. Chart 3 shows the share of imports plus exports traded with

the rest of euro area countries. The four countries show shares over 40%, with a slightly

declining trend over the last years. It is noticeable the large increase experienced by Spanish

imports and exports since 1986, the year Spain joined the European Union. The large share

7The other asset classes (FDI, fixed income and other assets) do also show a large share of euro areapositions after the introduction of the common currency.

8The data sources are the NSEE France, ISTAT Italy, and the central banks of Germany and Spain


of bilateral trade of the four countries with the rest of the euro area shows the potential

impact that the common currency may have induced to the evolution of the net external

imbalance, in this case through the trade channel of external adjustment.

Finally, Table 1 shows the estimates of real portfolio returns for assets and liabilities as well

as the return differentials. The table includes real returns for the complete sample as well

as for the periods before and after the introduction of the euro. The only country able to

obtain an average positive return differential over the whole period was Germany, with the

other countries experiencing, on average, larger returns on their foreign liabilities than on

their foreign assets. During the period after the introduction of the euro Spain was able to

generate positive return differentials on average, while the other countries presented negative

return differentials. The reduction of financing costs due to joining the euro area may have

influenced the positive return differential obtained by Spain.

In order to analyze the external adjustment process of a country Evans and Fuertes (2011)

derive the present value relation for the net external position using several log-linearizations

that include assumptions about the behaviour of different financial ratios9. I will next

summarize the main steps to obtain this present value equation, which will be used as the

starting point for the empirical analysis.

I start with the following equation:10

FAt − FLt ≡ Xt −Mt +RFAt FAt−1 −RFL

t FLt−1 (1)

9See Evans and Fuertes (2011) and Fuertes (2019)10The analysis does not include the secondary income which has been historically low for the four countries.

3 Empirical analysis

Where FAt and FLt are gross foreign assets and liabilities at the end of period t, Xt and Mt

are exports and imports during period t, all measured in terms of the consumption index.

RFAt and RFL

t represent gross real returns on foreign assets and liabilities between the end of

periods t− 1 and t. After several log-linearizations and some algebra I obtain the following

relation:

nfat ≈ rNFAt +

1− ρ

ρnxt−1 +

1

ρnfat−1 (2)

Where nfat is the log of the ratio of foreign assets to liabilities at the beginning of period

t. rNFAt is the log of the return differential of foreign assets and liabilities and nxt is the

difference of the log of exports minus imports. ρ is a discount factor. Defining nxat =

nfat + nxt and Δnxt = nxt − nxt−1 I obtain the following expression:

nxat ≈ rNFAt +Δnxt +

1

ρnxat−1 (3)


I impose the no-Ponzi game condition Et limi→∞ ρi(nxat+i) = 0 on the equation above to

rule out the possibility that a country defaults on its foreign claims. The next equation

shows the present value relation between the variable nxat and future expected portfolio

where εt is a vector of zero mean errors. The VAR has the following first order companion

representation:

Zt = AZt−1 + εt

11In deriving equation (4) I have performed several first order approximations. To assess the accuracy ofthose approximations we can compute the error term from equation (3) which also includes any measurementerrors from the original data. The error term is small and stationary for the four countries under analysis

Iterating forward equation (3) and taking expectations conditioned on period t information,

which includes de value of nxat , I obtain:

nxat ≈ −Et

∞∑i=1

ρi(rNFAt+i +Δnxt+i) + Et lim

i→∞ρi(nxat+i)

return differentials and net exports growth,11

nxat ≈ −Et

∞∑i=1

ρi(rNFAt+i +Δnxt+i) (4)

I will use nxat as the variable of interest that measures external imbalances, being the two

terms at the right hand side of the equation the valuation component and the trade compo-

nent respectively. This equation shows how current imbalances will be corrected in the future.

Equation (4) implies that the net external position can only vary if it forecasts changes in

portfolio returns or if it forecasts changes in net exports growth. If Et

∑∞i=1 ρ

irNFAt+i = 0, any

adjustment of the net external position will come from future changes in net exports growth

(trade component). On the other hand, if Et

∑∞i=1 ρ

iΔnxt+i = 0, any adjustment will come

from future changes in portfolio returns (valuation component).

Next we need to characterise the joint behaviour of the variables involved in equation (4) in

order to estimate the valuation and the trade components. This will allow us to test if there

are any changes in the net external position due to the introduction of the common currency

and it will also provide evidence on the different contributions of the valuation and trade

components depending on the foreign exchange regime. I follow the methods developed by

Campbell and Shiller (1987) (see also Evans and Fuertes (2011) and Fuertes (2019)). In

order to estimate the valuation and trade components I use a VAR formulation. First, I set

a VAR(p) representation with zt = (rNFAt ,Δnxt, nxat)

′. All variables are demeaned.

zt = A(L)zt−1 + εt


where Zt = (z′t, ..., z

′t−p+1) and εt = (εt, 0). Next, I define the vectors er, eΔnx, enxa such that

they select the different elements of Zt (for example e′rZt = rNFA

t ). I can express equation

(4) in terms of the VAR formulation.

e′nxaZt = −(e′

r + e′Δnx)

∞∑i=1

ρiEtZt+i

First of all I am going to test if we can identify any changes in the behaviour of the variables

included in the VAR specification at the time of the introduction of the euro. I will do so by

running structural break tests at unknown dates for a system of equations using the VAR

developed in the previous section 12. The results of the tests will provide evidence in favor

or against the potential role that the foreign exchange rate regime may have on the external

adjustment process. Qu and Perron (2007) provide a framework to analyze series with

multiple structural changes that occur at unknown dates in linear multivariate regression

models, such as VARs. The breaks may happen in the parameters of the conditional mean,

in the covariance matrix of the errors, or both, and the distribution of the regressors is also

allowed to change across regimes. This is important because the tests determine whether

or not the breaks in mean and variance happen at the same time. The framework used by

these authors is the following:

yt = (I ⊗ z′t)Sβt + ut

12Dickey-Fuller augmented unit root tests are performed to the three variables introduced in the VAR. Asit is expected, the tests for Δnx and rNFA reject the null of unit root at the 1 % level for all samples. Thetests for nxa cannot reject the null of unit root in the case of France and Germany. For Spain and Italy thenull is rejected at the 10 % level. There are several reasons to believe that the nxa variables are not unitroot processes though. First, nxa is by definition a linear combination of stationary variables given thatΔnx and rNFA are stationary. Second, the unit root tests lack of power when the alternative hypothesis is avery persistence process with high ρ as it is the case. Third, being nxa a non-stationary process implies thatthe non-ponzi game condition could be violated, meaning that Germany and France, with some probability,may not repay their external debt, something very unlikely over the last 40 years.

The valuation and trade components can be computed as follow:

nxart = e′rρA(I − ρA)−1Zt =

∞∑i=1

ρiAiE(rNFAt+i |Ω∗t )

3.1 Testing for Structural Breaks

nxaΔnxt = e

′ΔnxρA(I − ρA)−1Zt =

∞∑i=1

ρiAiE(Δnxt+i|Ω∗t )

In the next sections I will exploit the relations derived from the present value equation (4)

for the joint dynamics of rNFAt , Δnxt, and nxat, as well as the estimates of the valuation

and trade components to analyze the external adjustment process of France, Germany, Italy

and Spain.


13I carried out the procedure with a maximum number of breaks m = 3 and a trimming of 0.2, whichmeans that the minimal length required is 50 observations.

There are n equations and T observations, excluding the initial conditions if lagged dependent

variables are used as the regressors. The total number of structural changes in the system

is m and the break dates are denoted by the vectors (T1, . . . . . . , Tm) with the convention of

T0 = 1 and T(m+1) = T . A subscript j indexes a regime (j = 1, ...,m+1), a subscript t indexes

a temporal observation (t = 1, ..., T ), and a subscript i indexes the equation (i = 1, ..., n)

to which a scalar dependent variable yi, is associated. The parameter q is the number of

regressors and z, is the set that includes the regressors from all equations zt,= (z1t, ..., zqt)′.

Finally, u has zero mean and covariance matrix Σj for Tj−1 + 1 ≤ t ≤ Tj(j = 1, ...,m + 1).

When using a VAR model as in this case we have that zt = (yt−1, ..., yt−q), which contains

the lagged dependent variables. I use a VAR(1) following the results from the Akaike and

the Schwarz criteria that select the optimal number of lags.

In order to construct the test of the null hypothesis of no break versus the alternative

hypothesis of some unknown number of breaks between 1 and some upper bound M , I first

use the UDmaxLRT (M) and WDmaxLRT (M) double maximum tests to see if at least one

break is present. Then, if the test rejects this hypothesis, I consider a SEQT (l+1|l) sequentialprocedure obtained from a global maximization of the likelihood function and based on a

test of l versus l + 1 changes.13. The covariance matrix of the errors is allowed to change

and normality is assumed when testing for changes in the covariance matrix. We correct for

serial correlation in the residuals and construct the robust covariance matrix by the method

of Andrews (1991). No pre-whitening technique is applied. Finally, the distribution of the

regressors is allowed to change in order to construct the confidence intervals.

Table 2 shows the results for France. The test identifies a structural break in the behaviour

of the series that happen at the end of 1998. This is consistent with the introduction of

the euro having modified the behaviour of the net external position and the adjustment

process, potentially changing the relevance of the valuation and trade components as well.

The test identifies another two breaks for France, the next one in 2004 and the last one in

2009. These two breaks seem to be more related to the real economy although the first one

is more difficult to identify. After 2004 France began to experience negative current account

and trade balances, which may have crucially affected the external adjustment process. The

last break in 2009 should be related to the global financial crisis and the recession France

suffered over that time. The global financial crisis produced important disruptions both on

the financial and the real side of the economy and it is expected that these effects could have

affected the adjustment process both for the valuation and trade components.

Table 3 presents the results for Italy. In this case the test only identifies two breaks, one in

1992 and another one in 1999. Similarly to France there is a structural break at the time of

the introduction of the euro, providing further evidence on the change in the behaviour of


Finally, table 5 shows the results for Germany. The test identifies two structural breaks, one

in 1989 and another one in 2006. The case for Germany is relevant as it is the only country

that does not show a structural break at the time of the introduction of the euro. There could

be several reasons. First, we have to consider that Germany’s external imbalance can almost

be completely explained by the trade component, a result that will be documented in the

next section. Fuertes (2019) showed that the break in the US external position documented

at the end of fixed exchange rate regime was mainly driven by the valuation component.

It could be that Germany’s net external position was not affected by the introduction of

the euro as much as the ones from the other countries because the trade component almost

completely explains the behaviour of Germany’s external imbalance. Second, Germany is

the largest economy within the euro area and it is reasonable to think that the euro has

been behaving more similarly to the Deutsche mark than any other currency and this may

have produced a less impact on the external position. Moreover, the monetary policy of the

euro zone has also been implemented to a large extent according to needs of the German

14The exchange rate mechanism established that currency fluctuations had to be contained within a marginof 2.25% on either side of the bilateral rates (with the exception of the Italian lira, the Spanish peseta, thePortuguese escudo and the pound sterling, which were allowed to fluctuate by ±6%). The United Kingdomdid also abandon the exchange rate mechanism in 1992.

economy, specially before the global financial crisis, which may have reduced the impact of

the common currency. Germany’s external imbalance seems to have been more affected by

the reunification of the country in 1989 and by the global financial crisis. Both events are

detected as structural breaks in the test although the one related with the global financial

crisis is stablished a little bit early at the end of 2006.

the external imbalance due to the establishment of the common currency area. The break in

1992 could be related to another event affecting the nominal exchange rate as the Italian lira

was devaluated by 7% in September of 1992 and abandoned the exchange rate mechanism

(ERM) of the European Monetary System at that time14 . After this devaluation the Italian

economy experienced a large period of current account and trade surpluses.

Table 4 shows the result of the structural break test for Spain. There are three structural

breaks identified: one in 1993, another one in 1999 and the last one in 2007. The test

identifies again a structural break at the time on the inception of the euro. It identifies

another break in 1993 which, similarly to the case of Italy, should be related to events

affecting the exchange rate. Even though Spain did not abandon the ERM in 1992, the

currency disruptions in the European monetary system did also affect Spain, as the Spanish

government devalued the peseta by 5% in September of 1992. After that there were another

two devaluations during 1992 and 1993: a 6% devaluation in November of 1992 and a 8%

devaluation in May of 1993. This period do also coincide with a recession of the Spanish

economy in 1993, with the GDP growth reaching -1% that year.


The regression coefficients βr and βΔnx represent the share on the unconditional variance

of nxa explained by the valuation component nxar and the trade component nxaΔnx. I

can empirically estimate nxa, the valuation and trade components as well as the regression

coefficients βr and βΔnx using the VAR estimates. Let A denote the estimated companion

matrix from the VAR. The predicted value for the nxat based on our VAR estimates will be:

nxat = −(e′r + e

′Δnx)ρA(I − ρA)−1Zt

= nxart +nxaΔnx

t (6)

From the OLS regressions of nxart and nxaΔnxt on nxat, I can compute the variance contri-

bution of the estimated valuation and trade components. From this variance decomposition

of the net external position we can obtain the relative importance of the valuation and trade

components over the external adjustment process for each of the countries under analysis.

Table 6 shows this information for the period including both the years before and after the

introduction of the euro. For Germany and Spain the trade component has been more im-

portant for the external adjustment. For France, the relevance of the valuation and trade

components has been almost the same and for Italy the valuation component has been capa-

ble to explain a larger share of the variance of the net external position. We have to keep in

mind that the results are not completely comparable as the sample period is not exactly the

same due to data availability. The results for Germany are striking as the trade component

almost explains all the historical variance of the external position, being the contribution of

the valuation component negligible. Moreover, the valuation component for Germany has

moved in the opposite direction of the external imbalance, showing a negative covariance.

For France, Italy and Spain both the valuation and the trade components have moved in

the same direction as the external position. From these results we have to expect that if

the behaviour of Germany’s external imbalance remains similar to its historical trends, the

3.2 Valuation and Trade Effects

The results of the tests in the previous section show that the introduction of the common

currency did change the external adjustment process, at least for France, ItaIy and Spain.

Now I will use the estimates of the valuation and trade components in order to quantify

the contribution of each of them to the variance of the net external position. By doing so

with different sample periods I can assess how the external adjustment process have changed

after the introduction of the common currency. In order to find out the contribution of the

valuation and trade components to the external adjustment, I perform the following variance

decomposition:

1 =Cov(nxa, nxa)

V ar(nxa)=

Cov(nxar, nxa)

V ar(nxa)+

Cov(nxaΔnx, nxa)

V ar(nxa)

=βr + βΔnx (5)


reduction of its creditor position will come from a reduction in net exports. On the other

hand, France, Italy and Spain will reduce their debtor positions by a combination of increas-

ing net exports and positive return differentials, being the relative important of these two

forces different for each country. As I already mentioned, Spain will restore its balanced

position mainly through increasing net exports and Italy by positive return differentials. For

France both components of external adjustment will play a similar role.

Next I analyze the changes that the introduction of the euro may have induced into the

external adjustment process. Fuertes (2019) finds for the US that the valuation component

increased its relative importance after the end of the Bretton Woods system of fixed ex-

change rate in 1973. A floating exchange rate regime made the valuation channel to play a

more prominent role on the external adjustment process. With a floating exchange rate the

valuation component not only was affected by asset price changes but also by exchange rate

changes, adding an additional source of adjustment. Under the same rationale, the valuation

component may have decreased its relative importance in the external adjustment process

of the euro area countries once the euro was in place as the bilateral external portfolio po-

sitions among the countries of the union would only change due to asset price movements.

In any case, the Bretton Woods system is not completely equivalent to the introduction

of the euro as the change for the US was from a fixed to a floating exchange rate system

while euro area countries remain with a floating exchange rates against third currencies. We

have also to take into account that there have been other events that may have affected the

relative importance of the valuation and trade channels. For instance, the global financial

crisis triggered large asset price changes that may have affected the dynamics of the external

adjustment, increasing the role of valuation effects.

Table 7 shows the variance decomposition of the net external position between the valuation

and trade components since 1999. The results show that for Germany and Spain there is

an increase in the importance of the trade component over this period. For Spain, since

the introduction of the common currency, 80% of the variance of the external imbalance is

explained by the trade component, being this number 61% if we use the whole sample. After

the introduction of the common currency Spain will have to rely more on the trade channel

in order to restore its debtor position. Similarly, for Germany the introduction of the euro

has made the country to depend even more on decreases in net exports to reduce its creditor

position. The valuation channel has increased its negative covariance with Germany’s exter-

nal imbalance during this period, making even more difficult the future external adjustment

of its creditor position. France and Italy on the contrary have experienced an increase in the

percentage of the variance of its external imbalance explained by the valuation component

during the currency area period. This could be the result of larger asset price changes or

that exchange rate movements within the euro area countries before the introduction of the

euro were against the adjustment of the external positions of France and Italy, making the

common currency to facilitate the adjustment of the external imbalance.


Tables 8 and 9 present the variance of nxa explained by the exchange rate valuation compo-

nent and a exchange rate trade component before and after the introduction of the euro16.

The most important conclusions from these two tables are that the exchange rates do con-

15The trade weighted exchange rates are OECD real effective exchange rates. I calculated the financialweighted real exchange rates using the country portfolio weights that I used to calculate the portfolio returnsfor each of the different asset classes.

16In the case of France in table 8, due to the small sample available before 1999 I provide the results forthe whole sample instead

For Spain and Italy there has been a large decrease in the variance of nxa explained by the

exchange rate valuation component after the introduction of the euro. In the case of the

exchange rate trade component , it has negatively affected the external adjustment process

after 1999 in both cases. We can then conclude that for these two countries the common cur-

rency area has implied a less important role of the exchange rate in the external adjustment

and the need to rely in other mechanisms to restore the external balance. For Germany,

consistent with the tests of structural breaks that do not find any break in 1999, it seems

that there are not important changes on the contribution of the exchange rate components

between the two periods. For France, the most striking result is the large and negative con-

tribution of the exchange rate trade component during the euro period. Overall it is evident

that the reliance on the exchange rate as a tool to facilitate the external adjustment process

has largely diminished after the introduction of the euro.

17Recall that I obtain the exchange rate components by including in the VAR estimation the part of thereturn differentials and net exports growth contemporaneously related with the trade weighted and financialweighted real exchange rates

Even though the results on tables 6 and 7 show that the contribution of the valuation and

trade components have indeed changed since 1999, those changes can be related to other

factors not affected by the foreign exchange regime. In order to identify, at least to some

extent, the contribution of the exchange rate regime to the external adjustment process I

have calculated a exchange rate valuation component and a exchange rate trade component.

I use a trade weighted and financial weighted real exchange rates15 to obtain the part of

the return differentials and the net exports growth that is contemporaneously related to

these two real exchange rates. Then I include these exchange rate variables in the VAR

specification and compute the exchange rate trade and valuation components. These two

components will be used to compute the percentage of the variance of nxa that is explained

by the part of the valuation and trade components contemporaneously related to the real

exchange rate.

tribute to the valuation and trade components of external adjustment and also that after

1999 those contributions have changed. We should also notice that the exchange rate valu-

ation component has more relevance in the external adjustment process than the exchange

rate trade component , consistent with the fact that the exchange rate may affect net exports

with some time lags17.


3.3 Future Adjustment Path

We can also make an assessment of the future adjustment paths of the external positions for

each country by computing the future expected values of nxa and the valuation and trade

components. These paths should be consistent with the relative relevance of the valuation

and trade components for each country. We can also learn how long will take to restore the

external balance for each of the economies from their current debtor or creditor positions.

We can compute the future expected adjustment path for nxa using the following equation:

ETnxaT+k = ETΔknxaT+k + nxaT

We can also compute the future adjustment path of nxa if only the valuation or the trade

components would operate:

ETnxavT+k = ETΔ

knxavT+k + nxaT

ETnxatT+k = ETΔ

knxatT+k + nxaT

Chart 4 shows the future adjustment path for Germany, being the horizontal axes the number

of quarters ahead. The red line shows the future evolution of nxa while the blue and green

lines show the evolution of nxa if only the valuation or the trade component would operate,

respectively. As we have already documented previously almost all the adjustment will be

made through the trade channel. The green line evolves very closely to the adjustment path

for nxa. Given that the valuation component hinders the restoration of Germany’s external

balance, if the trade component would not play any role the external imbalance would result

in a slightly larger creditor position than the current one, as the blue line shows. If there

are not unexpected shocks affecting the future external adjustment, Germany will restore

its balanced position in 40 years. The convergence process will be much faster over the first

years, being able to reduce in half its creditor position in only 7 years.

Chart 5 shows Spain’s adjustment path. We can see again how it is consistent with previous

results that showed how the trade channel is the main driver of the external adjustment.

Spain would experience a fast convergence towards an external balanced position, taking

around 19 years to reach that point. It would only take 3 years to reduce in half its debtor

position. Chart 6 presents the adjustment path for France. In this case we can see how

both the valuation and trade components almost contribute equally to the restoration of

the external balance. For France it would take a long way to achieve the external balance

although it is the country with the smallest external imbalance. It will restore its external

balance in 25 years, being able to reduce it debtor position in half in 8 years. Finally chart

7 presents the future expected evolution of Italy’s external position. The contribution of the

valuation component to the external adjustment is larger than that of the trade component.


It is reasonable to think that, as it has happened in the past, there would be unexpected

shocks that will make the expected future adjustment paths depicted in charts 4-7 differ

18The quick external adjustment expected for Italy and Spain is supported by projections from the Inter-national Monetary Fund released in the April 2019 World Economic Outlook. These projections establishthat for a group of euro are debtor countries, including Italy and Spain, the net international investmentposition is expected to improve by more than 25 percentages points of their collective GDP over the period2017-2024

for different horizons k = {1, 4, 8}. Δket+k is the change in the real exchange rate (an

increase implies an appreciation of the currency) and FXdt is the dummy variable that

from the future evolution of the external imbalances. There is relevant information we can

obtain from this exercise though. For the two countries with the largest external imbalances,

Germany and Spain, agents expect they will to be able to reduce their creditor and debtor

positions by half in a relatively short period of time: 7 and 3 years respectively. The future

adjustment paths also show how all countries but Germany will need both from the valuation

and trade components to achieve their external balance. Only Germany could rely exclusively

on the trade channel, with the valuation channel playing almost no role at all.

3.4 Exchange Rate Predictability

The results from previous sections document the relationship between the net external posi-

tion and the exchange rate. It is then expected that the evolution of the external imbalance

may have some forecasting power over the foreign exchange. This explanatory power has

already been documented by Gourinchas and Rey (2007) and Evans and Fuertes (2011),

although none of these papers study the implications of different exchange rates regimes.

On the contrary, Fuertes (2019) analyse the forecasting power of the net external position of

the U.S. over the dollar, taking into account the foreign exchange regime. The results show

that the relationship between the U.S. external imbalance and the dollar changes at the end

of the Bretton Woods system of fixed exchange rates. I will next analyse if the inception of

the euro had a similar effect. I do check whether the exchange rate regime influences the

external adjustment process by regressing the changes in the real exchange rate on the net

external position, a dummy variable identifying the exchange rate regime and an interaction

term between the external position and the dummy. This interaction term will be the main

variable of interest given that a statistical significant coefficient will imply a different rela-

tion between the foreign exchange and the net external position depending on the nominal

foreign exchange regime. I compute the OLS estimates of

1

kΔket+k = α + β1nxat + β2FXdt + β3nxat ∗ FXdt + νt+k (7)

Italy will restore the external balance in around 18 years and it will reduce it by half in less

than 5 years18.


identifies the foreign exchange regime (equals one before the introduction of the euro). I

run the regressions separately for both the real trade weighted exchange rate and the real

portfolio weighted exchange rate. For comparison purposes, I also compute the regression

without the foreign exchange regime dummy and the interaction term.

Table 10 presents the results for Spain. The coefficient β3 is significant both for the portfolio

weighted and the trade weighted real exchange rates, implying that the inception of the

euro affected the relationship between the net external position and the exchange rates.

In particular, for the portfolio weighted real exchange rate, given that β1 is not significant

at any horizon in equation 7, we conclude that the forecasting power of nxa disappeared

after 1999, consistent with the decreased role played by the exchange rate in the external

adjustment process due to the common currency. As expected, the sign of the coefficients is

positive, meaning that a deterioration in the external imbalance implies a future exchange

rate depreciation. Finally, we should notice the large increase in the R2 when we run the

regression taking into account the different exchange rate regime. The R2 increases with

the exchange rate horizon, reaching a value of 0.26 when forecasting the evolution of the

exchange rate over the next two years.

The results for Italy are presented on table 11. They are very similar to those obtained for

Spain although there is an important difference. The external imbalance has a less forecasting

power for the trade weighted real exchange rate than for the portfolio weighted one. This

could be consistent with the fact that for Italy the valuation component has more relevance

than the trade component. The R2 for the evolution of the portfolio weighted real exchange

rate over the next two years reaches 0.36 in the regression that takes into account the change

in the foreign exchange regime. As it happened with Spain, the forecasting power of nxa

over the portfolio weighted exchange rate disappears after the introduction of the euro.

Table 12 shows the results for Germany. It is the country where the R2 are lower, imply-

ing the weakest forecasting power of the external imbalance over the exchange rate among

the four countries. The coefficient β3 is only significant at the two year horizon and the

regression forecasting the trade weighted real exchange rate provides more significant coef-

ficients and a larger R2, consistent with the trade component having a more important role

in the external adjustment of this country. The main difference with respect to previous

results is the negative sign of the coefficient β1 in the regression that takes into account the

foreign exchange regime. The negative coefficient implies that after 1999 an improvement

of Germany’s external imbalance forecasts a depreciation of the euro. This result provides

interesting insights about the external adjustment process within a currency union. After

1999 the net external position of Italy and Spain deteriorated while Germany’s one improved.

We have documented for Italy and Spain, since 1999, that a deterioration of the external

imbalance implied a future depreciation of the trade weighted real exchange rate. During

the same period Germany improved its external imbalance, what required a future appre-

ciation of the currency in order to facilitate the external adjustment. The negative sign of


The accuracy in estimating portfolio returns has been a topic of ample debate in the lit-

erature. In the case of the U.S. a first wave of studies calculated portfolio returns implied

from U.S. NIIP data (see Lane and Milesi-Ferretti (2005); Meissner and Taylor (2006) and

Obstfeld and Rogoff (2005)), obtaining large return differentials between portfolio assets and

liabilities. Later, Curcuru et al (2008) argued that these implied returns were upward biased

due to inconsistencies in the different sources of data for flows and positions. They calculate

portfolio returns from market prices, as Gourinchas and Rey (2007) do, obtaining smaller

return differentials. Recent research from the BEA, the compilers of the NIIP data, does also

find lower estimates of portfolio return differentials than those obtained from the implied

returns in the first wave of papers, pointing out that NIIP data should not be used to obtain

returns (see Gohrband and Howell (2015)).

In this paper I computed returns from market prices in order to obtain quarterly return

differentials for a period that includes both the years before and after the introduction of the

euro. I do not claim that the implied returns may have any inconsistencies for the countries

under analysis19 as it is the case for the U.S., but I needed to construct a data set that

includes the period before the introduction of the euro. Unfortunately I could not obtain

quarterly implied returns for the yeas before 1999 due to data limitations and the only option

was to estimate returns from market prices.

19Habib (2010) analyses the differential returns between gross foreign assets and liabilities for a sample of49 countries, including France, Germany, Italy and Spain, using yearly implied returns

The results from tables 10 - 13 provide two important messages. First, the relationship

between the external imbalance and the future evolution of exchange rates is affected by

the foreign exchange regime. Second, this relationship could be different for each country

within a currency union, helping or jeopardising the external adjustment process depending

on holding a debtor or a creditor position.

4 Robustness Checks

β1 may indicate that the behaviour of the euro has been driven by the needs of external

adjustment of deficit countries such as Italy and Spain, compromising the adjustment of

Germany’s external position as foreign exchange movements affect differently debtor and

creditor countries.

Finally, table 13 present the results for France. The β3 coefficients are significant and the R2

increases significantly when running the regressions taking into account the foreign exchange

rate regime. The main difference with previous results is the negative coefficient β3 , implying

that before 1999 a deterioration in France’s external imbalance forecasts an appreciation of

the french franc. After the introduction of the euro the forecasting power of nxa shows the

expected relationship as β3 coefficients are positive.


The equation above includes a set of restrictions on the coefficients of the VAR that repre-

sent constraints on the joint dynamics of rNFAt , Δnxt, and nxat. They can be empirically

examined by computing a Wald test from the estimates of the A matrix obtained as the OLS

estimates of the VAR equations.

returns we cannot reject the null that equation (9) holds. On the contrary, the Wald test

rejects the null when using the market based returns. We should keep in mind that the mean

square errors of nxat are very low using either market based returns and derived returns.

The results of the Wald test indicate that the market based returns may have incurred in

some inconsistencies that may reduce the accuracy of our estimates of the valuation and

trade component, being the implied returns more accurate to describe the joint behaviour of

rNFAt , Δnxt, and nxat. For the case of France the Wald test rejects the null that equation

(9) holds, with the MSE being larger for the predicted nxat when using the implied returns.

In this case it seems that the market based returns are more accurate. We should keep in

Table 14 present the results of the Wald test on the above equation as well as the mean square

errors of the predicted nxat using the market based derived returns (DR) and the implied

returns (IR). For Germany, Italy and Spain the Wald test shows that using the implied

Then, a natural robustness check is to compute the implied returns for the years avaialble

and compare the approximation accuracy of our different estimates using the market based

returns and the implied ones. I will also assess if the main results and conclusions change

when using implied returns. In section 3.2 we already showed that the estimates of the

valuation and the trade component together are able to explain the whole variance of the

actual nxa. This is a first proof of the quality of our approximation for the present value

equation (4). Another way to asses the accuracy of our approximation is to compute the

mean square error of the difference between the actual nxa and the predicted nxat, which is

obtained as the sum of the estimates of the valuation and trade components. Finally, we can

also assess the accuracy of the estimates by checking if the present value equation (4) holds

using the forecasts from the VAR. In order to do we first obtain the following expression

from the present value equation (4):

e′nxaZt =− (e

′r + e

′Δnx)

∞∑i=1

ρiAiZt

=− (e′r + e

′Δnx)ρA(I − ρA)−1Zt

(8)

This equation must hold for all possible values of Zt, such that the companion matrix A

from the VAR must satisfy

e′nxa =− (e

′r + e

′Δnx)ρA(I − ρA)−1 (9)


mind that even though the Wald test rejects that equation (9) holds when using the market

based returns, the estimates of the valuation and trade component obtained produce very

low approximation errors and they are capable to explain the whole variance of the actual

nxa.

Because of that and despite the fact that the market based returns show some degree of incon-

sistencies for Germany, Italy and Spain, our main concern is to asses if those inconsistencies

spotted out in the results of the Wald tests are large enough to invalidate the conclusions

documented in the previous sections. In particular we should be concerned about the ca-

pability of the valuation and trade components to accurately portrait the behaviour of the

net external position. Given that we have already showed that using the implied returns we

obtain estimates of the valuation and trade components that provide a good approximation

of the present value equation (4), we next evaluate how different these estimates are when

using the market based return.

Table 15 shows the correlation coefficients for different series obtained using market based

returns and derived returns. The first two columns show the correlation of the estimates of

the valuation and trade components obtained using the different return differentials. The

correlation coefficients are very close to one, signalling that the behaviour of the series is

almost the same no matter the returns used. The third column assess the correlation between

the predicted nxat using the two different series of return differentials, showing again that

both are pretty similar. Finally, the last two column show the correlation between the

actual nxa and the predicted nxat using the implied returns and the market based returns

respectively. Even though the correlations are larger for the series computed using implied

returns, except for France, the correlations are also high when using market base returns. By

these metrics we can conclude that the analysis using market based returns remains valid.

Finally, I have replicated the results from table 7 using the two types of returns. Table

16 presents the percentage of the variance of nxa explained by the valuation and trade

components computed using implied returns and market based returns. The results remain

qualitatively the same no matter the series of return used. The relative relevance of the valu-

ation and trade components do not change and the percentage of variance explained is almost

the same independently of the returns used. The only country that shows some differences

is Italy although the valuation component remains as the main channel of adjustment.

Overall, even though for Germany, Italy and Spain the implied returns are more accurate to

describe the joint dynamics of rNFAt , Δnxt, and nxat embedded in the present value equa-

tion (4), using the market based returns provides the same conclusions about the external

adjustment process and the estimates of the valuation and trade components are almost the

same. We can then be pretty comfortable with the results obtained in the previous sections.


I analyze the external adjustment path of the four main economies of the euro area, covering

both the period before and after the introduction of the euro, to understand if the currency

area affected their external adjustment process. I find a structural break in the net external

position for all countries but Germany at the time of the introduction of the euro, pointing

out that the inception of the common currency changed the external adjustment process.

The fact that Germany does not show this structural break is consistent with the exchange

rate regime mainly affecting the valuation channel of external adjustment, given that the

variance of Germany’s net external position is almost completely explained by the trade

channel. The importance of the valuation component of external adjustment increases after

the introduction of the euro for France and Italy, and decreases for Germany and Spain.

Third I also find that France and Italy will adjust the net external position mainly through

the valuation component of external adjustment, while Germany and Spain will restore their

The results of the paper continue the debate for policy analysis on the benefits of a fixed or a

floating exchange rate regime to correct external imbalances. I document adverse valuation

effects that difficult the correction of external imbalances for the case of Germany. Even

though this should not be a matter of concern as Germany enjoys a creditor position and

reaching the external balance should not be crucial, adverse valuation affects could be dan-

gerous in other situations. For example, emerging countries with a relevant share of foreign

currency liabilities and large debtor positions, could be affected by a local currency depre-

ciation as it may trigger large valuation effects that further increase their debtor positions.

The findings in this paper do also reveal the need to change the mechanisms of external

adjustment once a common currency is in place. Being the nominal exchange rate fixed

among the countries of the currency union, other adjustment mechanisms such as internal

devaluation and the change in the relative price levels. may operate. It is also important

to notice that being part of a currency union may hinder the external adjustment process

of a country as the adjustment needs are different for debtor and creditor countries. For

instance, as it is documented in this paper, the real exchange rate have evolved according

to the adjusting needs of debtor countries such as Italy and Spain, pushing towards larger

external positions of creditor countries such as Germany.

5 Conclusion

external balance mostly through the trade component.

The process of external adjustment for a country within a common currency area has received

little attention in the literature, despite the fact that an important mechanism of correction

of imbalances, the nominal exchange rate, has been partially cancelled. Changing from a

floating to a fixed exchange rate regime within a currency area may difficult the external

adjustment and could be potentially dangerous for countries with large negative external

positions. Understanding how the external adjustment process has evolved over time for the

countries of the euro area and the implications of the introduction of the euro are the main

research questions of the paper.


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[33] Qu, Z. and Perron, P. (2007). Estimating and Testing Structural Changes in Multivariate

Regressions. Econometrica, 75(2), 459-502.


Figure 2: Portfolio Equity Weights for Euro Area Positions

Figures

-150

-100

-50

0

50

NIIP/GDP (2017)%

Figure 1: Net International Investment Position to GDP ratio

40

50

60

70

80

90

100

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016France Germany Italy Spain

%

30

35

40

45

50

55

60

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

Spain France Italy Germany

%

Figure 3: Exports plus Imports Weights for Euro Area Trade


Figure 5: SPAIN: Future Adjustment Path

-0.1

0

0.1

0.2

0.3

0.4

0.5

0 20 40 60 80 100 120 140 160 180

Future Adjustment Path: GERMANY

Valuation Trade NXA

Figure 4: GERMANY: Future Adjustment Path

-0.48

-0.4

-0.32

-0.24

-0.16

-0.08

0

Future Adjustment Path: SPAIN

Valuation Trade NXA

Figure 6: FRANCE: Future Adjustment Path

-0.08

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0

0 20 40 60 80 100 120 140 160 180

Future Adjustment Path: France

Valuation Trade NXA


Sequential test (l+1/l)

Wdmax l=1 l=2 Number of Breaks

58.578*** 30.565*** 36.170*** 3

Date

Break I 1998:IV 1998:I 2001:III

Break II 2004:I 2003:I 2004:II

Break III 2009:II 2008:III 2010:IV

CI (90%)

Notes: Maximun number of breaks M = 3 and trimming = 0.2; The covariance matrix of the erros is allowed to change and normality is assumed when testing for changes in the covariance matrix; serial correlation in the residuals and robust covariance matrix is constructed by the method of Andrews (1991); No pre whitening technique is applied; The distribution is allowed to change in order to construct the confidence intervals. *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively.

Figure 7: ITALY: Future Adjustment Path

-0.09

-0.08

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0

0 20 40 60 80 100 120 140 160 180

Future Adjustment: Italy

Valuation Trade NXA

Difference Claims Liabilities Difference Claims Liabilities Difference Claims LiabilitiesFrance -0.76 2.87 3.63 -1.22 5.65 6.87 -0.56 1.43 1.99Germany 0.38 4.04 3.65 1.26 6.53 5.28 -0.49 1.54 2.03Italy -1.18 2.99 4.17 -2.20 4.94 7.14 -0.15 1.04 1.19Spain -0.36 4.09 4.45 -1.58 6.03 7.61 0.92 2.03 1.11Note: The data shows the average of quarterly returns annualized.

All Sample Pre-euro period Euro period

Tables

TABLE 2 - FRANCE: Analysis of Structural Breaks (Qu and Perron Methodology)

TABLE 1: RETURN DIFFERENTIALS COMPARISON (%)




88.711*** 36.509*** 29.914* 3

Date

Break I 1993:I 1992:I 1994:I

Break II 1999:II 1998:II 1999:III

Break III 2007:IV 2007:I 2010:I

CI (90%)




122.679*** 68.714*** 25.019 2

Date

Break I 1992:II 1992:I 1994:II

Break II 1999:IV 1995:III 2000:I

CI (90%)


TABLE 3 - ITALY: Analysis of Structural Breaks (Qu and Perron Methodology)

TABLE 4 - SPAIN: Analysis of Structural Breaks (Qu and Perron Methodology)


Country Sample Valuation Component Trade Component

France 1999 - 2016 54.60 45.39

Germany 1999 - 2016 -21.86 121.85

Italy 1999 - 2016 65.87 34.12

Spain 1999 - 2016 19.48 80.51



75.006*** 35.081*** 25.623 2

Date

Break I 1989:II 1987:II 1990:III

Break II 2006:III 2005:II 2006:IV

CI (90%)


TABLE 5- GERMANY: Analysis of Structural Breaks (Qu and Perron Methodology)

Country Sample Valuation Component Trade Component

France 1990 - 2016 50.81 49.18

Germany 1980 - 2016 -1.67 101.66

Italy 1980 - 2016 56.32 43.67

Spain 1985 - 2016 39.06 60.93

TABLE 6: UNCONDITIONAL VARIANCE DECOMPOSITION OF NET EXTERNAL POSITION

TABLE 7: UNCONDITIONAL VARIANCE DECOMPOSITION OF NET EXTERNAL POSITION


The numbers represent the unconditional variance of nxa explained by the part of the valuation and trade components that is contemporaneoulsy related to the foreign exchange. Due to the small sample size before 1999 the figures for France are computed using the whole sample.

The numbers represent the unconditional variance of nxa explained by the part of the valuation and trade components that is contemporaneoulsy related to the foreign exchange.

TABLE 8: UNCONDITIONAL VARIANCE OF NXA EXPLAINED BY EXCHANGE RATES(BEFORE 1999)

*, ** and *** denote significance at the 10, 5 and 1% levels, respectively.

HORIZON 1 4 8 1 4 8

0.0098 0.0198*** 0.0219*** 0.0014 0.0128* 0.0165***(0.0116) (0.0052) (0.0041) (0.0160) (0.0071) (0.0064)

0.0153 0.0163 0.0168*(0.0248) (0.0120) (0.0094)

R2 0.0071 0.0862 0.1749 0.0120 0.1166 0.2619

Trade Weighted Trade Weighted

Country Sample FX Valuation Component FX Trade Component

France 1990 - 2016 -5.71 3.37

Germany 1980 - 1998 15.56 -2.95

Italy 1980 - 1998 15.27 3.01

Spain 1985 - 1998 11.28 11.02

TABLE 9: UNCONDITIONAL VARIANCE OF NXA EXPLAINED BY EXCHANGE RATES(SINCE 1999)


France 1999 - 2016 14.09 -20.06

Germany 1999 - 2016 15.63 2.33

Italy 1999 - 2016 3.77 -2.12

Spain 1999 - 2016 3.59 -6.49

TABLE 10: FORECASTING EXCHANGE RATES WITH NET EXTERNAL POSITION.SPAIN

HORIZON 1 4 8 1 4 8

0.0117 0.0174*** 0.0184*** -0.0039 -0.0008 0.0068(0.0135) (0.0063) (0.0043) (0.0192) (0.0077) (0.0064)

0.0282 0.0340*** 0.0274***(0.0282) (0.0124) (0.0088)

R2 0.0073 0.0603 0.1205 0.0187 0.1328 0.2675

Portfolio Weighted Portfolio Weighted


HORIZON 1 4 8 1 4 8

0.0102 0.0102* 0.0108** 0.0077 0.0086 -0.0025(0.0147) (0.0060) (0.0043) (0.0147) (0.0082) (0.0067)

0.0026 0.0012 0.0158*(0.0243) (0.0113) (0.0086)

R2 0.0040 0.0161 0.0325 0.0043 0.0173 0.0412


*, ** and *** denote significance at the 10%, 5% and 1% levels, respectively.

HORIZON 1 4 8 1 4 8

0.0378 0.0404*** 0.0397*** -0.0020 0.0021 0.0071(0.0242) (0.0147) (0.0092) (0.0096) (0.0067) (0.0065)

0.0554 0.0526** 0.0444***(0.0376) (0.0213) (0.0130)

R2 0.0237 0.0872 0.1621 0.0560 0.1925 0.3605



TABLE 11: FORECASTING EXCHANGE RATES WITH NET EXTERNAL POSITION.ITALY

HORIZON 1 4 8 1 4 8

0.0070 0.0196 0.0241*** -0.0042 0.0126 0.0232**(0.0225) (0.0141) (0.0087) (0.0188) (0.0128) (0.0098)

0.0176 0.0106 0.0013(0.0374) (0.0232) (0.0151)

R2 0.0012 0.0241 0.0708 0.0035 0.0269 0.0710


TABLE 12: FORECASTING EXCHANGE RATES WITH NET EXTERNAL POSITION.GERMANY

HORIZON 1 4 8 1 4 8

-0.0012 0.0054 0.0075** -0.0100 -0.0038 -0.0232***(0.0107) (0.0056) (0.0035) (0.0211) (0.0118) (0.0082)

0.0091 0.0096 0.0359***(0.0247) (0.0136) (0.0092)

R2 0.0001 0.0052 0.0209 0.0070 0.0136 0.0826



HORIZON 1 4 8 1 4 8

-0.0082 0.0075 0.0009 0.0282 0.0303** 0.0334***(0.0138) (0.0084) (0.0060) (0.0184) (0.0146) (0.0095)

-0.0364 -0.0374* -0.0567***(0.0314) (0.0198) (0.0113)

R2 0.0042 0.0089 0.0003 0.0221 0.0669 0.2673


TABLE 13: FORECASTING EXCHANGE RATES WITH NET EXTERNAL POSITION.FRANCE

Country Sample Wald Test (p-value) MSEFrance

DR 1999-2016 0.0084 3.86E-05IR 1999-2016 0 9.00E-05

GermanyDR 2004-2016 0 6.91E-05IR 2004-2016 0.9520 3.23E-07

ItalyDR 1999-2016 0 1.62E-04IR 1999-2016 0.1454 1.90E-06

SpainDR 1999-2016 0 4.89E-04IR 1999-2016 0.7266 1.04E-06

TABLE 14: ESPECIFICATION TEST AND APPROXIMATION ERROR

returns ( )

HORIZON 1 4 8 1 4 8

-0.0030 -0.0066 -0.0102*** 0.0055 0.0078 0.0095*(0.0098) (0.0055) (0.0037) (0.0149) (0.0086) (0.0058)

-0.0192 -0.0285** -0.0388***(0.0243) (0.0129) (0.0069)

R2 0.0006 0.0123 0.0687 0.0059 0.0599 0.2746




Country Valuation

ComponentTrade

Component

France 0.96325 0.99608 0.98128 0.99127 0.99582

Germany 0.99228 0.99574 0.99278 0.99996 0.99182

Italy 0.96689 0.99459 0.99036 0.99986 0.98880

Spain 0.98830 0.99115 0.99216 0.99995 0.97925

TABLE 16: UNCONDITIONAL VARIANCE OF NXA EXPLAINED BY EXCHANGE RATESDERIVED RETURNS (IMPLIED RETURNS)

TABLE 15: CORRELATIONS BETWEEN SERIES OBTAINED USING IMPLIED AND DERIVED RETURNS

The numbers represent the unconditional variance of nxa explained by the part of the valuation and trade components that is contemporaneoulsy related to the foreign exchange.


France 1999 - 2016 54.6 (58.8) 45.4 (41.2)

Germany 1999 - 2016 -21.9 (-23.6) 121.8 (123.6)

Italy 1999 - 2016 65.9 (51.2) 34.1 (48.8)

Spain 1999 - 2016 19.5 (16.2) 80.5 (83.8)

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